System and method for electronically managing medical data files in order to facilitate genetic research

ABSTRACT

A method for conducting genetic research on medical data. The method includes the step of accessing a database storing a plurality of medical records associated with a plurality of individuals, each medical record including at least one unique identifier associated with a certain individual and medical data associated with the certain individual. The method also includes the steps of extracting from the database the medical data associated with at least a subset of the plurality of individuals and, for each individual of the subset, obtaining electronically stored genetic data associated with the respective unique identifier. Also, the method includes processing the extracted medical data and obtained genetic data for attempting to identify an association between particular genetic data and a particular medical condition.

The present application is a Continuation-In-Part of U.S. patentapplication Ser. No. 09/735,585 filed Dec. 13, 2000 now U.S. Pat. No.6,775,670, which is a Continuation-In-Part of U.S. patent applicationSer. No. 09/087,843 filed May 29, 1998, which issued as U.S. Pat. No.6,263,330 on Jul. 17, 2001.

FIELD OF THE INVENTION

The present invention relates to the field of information distributionsystems. More specifically, the invention pertains to a system andmethod for the electronic management of medical data files, enablingcomplex genetic research to be conducted on the medical data containedin those files.

BACKGROUND OF THE INVENTION

In the past few years, the worlds of information and technology havemade important evolutions. We have progressed from a universalanalogical support, usually on paper, towards a theoretically universalelectronic support based on the multimedia as well as Internet Protocol(IP) based technology such as the World Wide Web (WWW), JAVA™ and ICQ™(I Seek You). The transmission of information has also made tremendousprogress and is already, or will be soon, practically instantaneous nomatter the form of information: text, data, sound, fixed or animatedimage.

The search for information is becoming more and more similar to theconcept of navigation among diverse sources of information and evenwithin documents themselves. The concept of navigation itself impliesthe need for user accessible tools as well as some sort of structuredorganization.

Narrowing the focus, this major revolution of information systems bringsabout profound changes in the relations between academic and hospitaldomains, in particular everything which deals with medical archives anddatabases as well as the ability to consult aggregates of these in atransparent way and to share in real or delayed time the informationobtained. The number of information sources is multiplying and thecommunication networks are proliferating: more and more documentation isavailable in digital form and the information highway is rapidlyexpanding. Concerning medical archives and databases, questions arise asto their role of maintaining or distributing information. If their rolesof acquiring, cataloging, and maintaining information are to continue,they will have to give access to the available information on newmultimedia supports as well as serve as access points to the informationwithin enlarged networks (e.g., the Healthcare Inforoute™). Thesechanges will add to the complexity of their management, all the whileenlarging their traditional mandate.

In other words, the medical archives and databases of the future willnot only be locally archived medical-legal clinical documents, but alsohigh-performance data banks of primary importance to the practice ofmedicine and health care everywhere within our network, all the whileconstituting a living core dedicated to clinical and scientific researchand development.

The above described evolution of the medical file and database systemrequires that the following two objectives be achieved:

-   -   effective navigation across multiple and diverse sources of        information, both local and distant, performed in a transparent        way with respect to the end user; and    -   efficient file management allowing universal research, the        treatment of contained information, and the sharing of        information between system users.

Currently, in order to store medical archives and databases, passivedata accumulation for each medical facility takes place within a localnetwork. Unfortunately, the costs of stocking information and storingfiles in a local network are quite high and the space available islimited. There is also a well-established historical insufficiencyconcerning the ability of the local medical archive file networks torespond to the documentary and informational needs of the emergencydoctor, the consultant, the bio-statistician, or the genetic researcher.The medical facilities do not have access to a complete ensemble ofinformation sources, thus complicating emergency medical procedures anddiagnoses all the while hampering the facility's ability to givepatients the most appropriate treatment.

Although the solution of combining the multiple independent localnetworks into a single integrated health network seems viable, theimplementation of such a concept presents certain problems concerningthe manner in which medical data is currently recorded and treated, atboth text and image levels. First of all, each separate medical facilitymay count up to hundreds of thousands of active files, some archivedlocally, others externally, either in an integrated or a refined form.Second of all, the file organization may be different at each facility,which is a huge obstacle to the merging of all files into a system thatsupports a common format file organization. There is also the problem ofavailable space when considering the large volume of informationcontained in each file and the fact that the life of a particularmedical file may approach up to twenty-five years in length. Thus volumeand merging problems lead to the conclusion that it is currently almostimpossible to combine and digitize the whole of all local medicalrecords from all local networks.

Even if the merging and digitizing were possible, there is a question asto whether this would be desired. The data recorded in the medical filesdoes not all have the same informational and discriminatory value in thelong run. In fact, the data falls into three categories: data withstrict medical-legal value, data with short-term clinical value, anddata with historical value or a biological signature. Unfortunately, thefirst category, data with strict medical-legal value, makes up themajority of data recorded in the file while it represents the leastvaluable information for emergency doctors, consultants,bio-statisticians, and genetic researchers. On the other hand, the mostvaluable information for emergency procedures and diagnoses, the thirdcategory, makes up a very small portion of data recorded in the file.Therefore, an integrated file management system which combines all ofthe information currently held in archived medical files would beextremely inefficient in terms of usage of space, thus impairing theextraction of information pertinent to a particular research.

It is therefore desirable to provide a method for developing theinformation highway to allow for access to shared medical files in anenlarged health network and other external databases in order toincrease the number of available sources of information for doctors andconsultants.

Such an enlarged health network may potentially contribute toadvancements in genetic research, which is currently in its early stagesof development. In particular, genetic researchers engaged in theidentification of links or associations between an individual's geneticdata and medical disease outcomes require much information to carry outtheir studies. As such, a regularly updated database of genetic andmedical information would be a potential gold mine of data to theseresearchers.

An existing method for identifying associations between genetic data andmedical disease outcomes is to conduct an epidemiological study.Epidemiology is a branch of medical science that deals with theincidence, distribution, and control of disease in a population.Epidemiological studies include, but are not limited to, case controlstudies, cohort studies, prospective, retrospective, and longitudinalstudies.

In a case control study, people having a disease of interest areidentified, then compared with a suitable control group of peoplewithout the disease. A cohort study involves two groups (cohorts) ofpatients, one of which received the exposure of interest and one ofwhich did not. Both groups in the cohort study are studied for theoutcome of interest. In a prospective study, subjects are followed froma given point in time and into the future, whereas in a retrospectivestudy, outcomes have occurred to the subjects before the study has evencommenced. Finally, a longitudinal study is a study in which the samegroup of individuals is interviewed at intervals over a period of time.

It is apparent that any one of these different types of epidemiologicalstudies involves a limited number of subjects, which in turn limits theamount of data that can be obtained for research purposes. Furthermore,not only is the pool of data restricted by the number of peopleparticipating in a study, but also by the amount of genetic and medicaldata that can feasibly be obtained for each participant. It is notedthat acquiring genetic data is a relatively complex and expensive task.Moreover, because the subjects in an epidemiological study must beobserved and often followed over a period of time, this method ofresearch is time consuming and requires a considerable amount of humanresources.

Thus, a need clearly exists for a system and method of electronicallymanaging medical data files, in order to facilitate research on theassociations between genetic data and medical disease outcomes.

SUMMARY OF THE INVENTION

In a broad aspect, the present invention is directed to a method forconducting genetic research on medical data. The method includes thestep of accessing a database storing a plurality of medical recordsassociated with a plurality of individuals, each medical recordincluding at least one unique identifier associated with a certainindividual and medical data associated with the certain individual. Themethod also includes the steps of extracting from the database themedical data associated with at least a subset of the plurality ofindividuals and, for each individual of the subset, obtainingelectronically stored genetic data associated with the respective uniqueidentifier. Also, the method includes processing the extracted medicaldata and obtained genetic data for attempting to identify an associationbetween particular genetic data and a particular medical condition.

In another broad aspect, the invention provides a method for conductinggenetic research on medical data of a network system. The network systemincludes at least one server managing a database, the databasecontaining a plurality of medical records associated with respectiveindividuals, each medical record including at least one uniqueidentifier associated with a certain individual and a collection ofmedical data elements associated with the certain individual, thecollection of medical data elements including genetic data and healthstatus information. The method includes the steps of accessing at leasta subset of the medical records stored in the database and extractingthe genetic data and health status information from the subset ofmedical records. The method also includes the step of providing theextracted genetic data and health status information to an adaptiveexpert system capable of processing the extracted genetic data andhealth status information in order to attempt to identify an associationbetween particular genetic data and a particular medical condition.

In yet another broad aspect, the present invention is directed to acombination of a network server having a first database storing aplurality of medical records associated with respective individuals, asecond database storing a plurality of medical files associated withrespective individuals, and an adaptive expert system. Each medicalrecord of the first database has at least one unique identifierassociated with a certain individual and a collection of medical dataelements associated with the certain individual, the collection ofmedical data elements including health status information. Each medicalfile of the second database has at least one unique identifierassociated with the respective individual and genetic data associatedwith the respective individual. The adaptive expert system can extractfrom the first and second databases the health status information andgenetic data associated with at least a subset of individuals, and isoperative to process the extracted genetic data and health statusinformation in order to attempt to identify an association betweenparticular genetic data and a particular medical condition.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of the present invention will become apparentfrom the following detailed description, considered in connection withthe accompanying drawings. It is to be understood, however, that thedrawings are provided for purposes of illustration only and not as adefinition of the boundaries of the invention, for which referenceshould be made to the appending claims.

FIG. 1 is a block diagram of a generic client-server environment, whereclients and server are linked by a local area network (LAN);

FIG. 2 is a flowchart depicting the current diagnostic process thattakes place in medical facilities;

FIG. 3 is a block diagram of the health inforoute integrated with theNetwork Distributed Shared Medical Record (NDSMR) System, in accordancewith an embodiment of the present invention;

FIG. 4 is a flowchart depicting the diagnostic process which will takeplace in medical facilities under the NDSMR System, in accordance withan example of implementation of the present invention;

FIG. 5 is a block diagram of a general client-server architecture;

FIGS. 6A, 6B, and 6C represent the NDSMR document layout in accordancewith an embodiment of the present invention;

FIG. 7 is a block diagram of a server in accordance an embodiment of thepresent invention;

FIG. 8 is a flowchart illustrating the operation of a program element inthe server shown in FIG. 7, in accordance with an example ofimplementation of the present invention;

FIG. 9 is a flowchart of the update process performed by the archivistson the NDSMRs, in accordance with an example of implementation of thepresent invention; and

FIG. 10 is a block diagram of the search engine (query) processimplemented by the NDSMR system, in accordance with an embodiment of thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates a generic client-server environment, enabled by alocal area network (LAN) 100. Client-server computing is a cooperativerelationship between one or more clients and one or more servers. Theclients 104, 106, 108, and 110 submit requests to the server 102, whichprocesses the requests and returns the results to the clients. Althoughthe processing is initiated by the client(s), both client(s) and servercooperate to successfully execute an application. Therefore, theinteraction between the client and the server processes is atransactional exchange in which the client is proactive and the serveris reactive. In addition to client(s) and server, the third essentialcomponent of the client-server environment is the network. Client-servercomputing is distributed computing. In other words, users, applications,and resources are distributed in response to business requirements andare linked by a single LAN 100 or by an Internet of networks.

Currently, most medical facility archives still operate on a paper-basedsupport system. The higher-end medical facilities are set up with theirown LAN for archiving medical files, however, and the computing systemis often modeled after the client-server system shown in FIG. 1. Sinceeach separate facility has its own LAN for archiving files, theaccessibility to files of a particular LAN is limited to theworkstations linked to that particular LAN.

FIG. 2 depicts an example of the current state of affairs faced bymedical facilities. Assume an ambulance delivers an unconscious patientto the emergency room (ER) at step 200. At step 202, the doctor makes aninitial diagnosis, but needs access to the patient's medical history inorder to prevent any misdiagnosis. If the patient is withoutidentification of any kind, a question asked at step 204, the doctor hasno other recourse but to administer a treatment at step 208 based on adiagnosis that is potentially inaccurate because it has been establishedstrictly on the patient's current medical condition, without taking intoaccount his/her previous medical history. If the patient does have anidentification of some kind, it can be used to cross-reference all ofthe hospital's medical files, archived locally and/or at assignedexternal archives, at step 206. The patient's file will only be found,at step 210, if the patient was previously treated at the same hospitaland already has a file stored in the network server's database. If thefile is not found, the doctor is back to step 208. Even if the file isfound, it is often incomplete and inaccurate as it lacks the informationconcerning treatment(s) administered in other medical facilities.Therefore, at step 212 the doctor must make a final diagnosis andperform the corresponding treatment.

FIG. 3 depicts an integrated health network embodying the principles ofthis invention. For the purposes of this specification, the word“integrated” implies the implementation of internetwork communicationbetween all of the various medical facility LANs, each having one ormore client workstations 304, as well as with external sources such asthe global Internet, the pharmaceutical network, on-line medicallibraries and journals, among many other possibilities. An importantcomponent of this network is a Network Distributed Shared Medical Record(NDSMR) system that includes two main components, a server 300 and aNDSMR database 302, with the potential for each LAN within the healthnetwork to be connected to the server 300. Alternatively, the system mayinclude more than one server, all operating inter-cooperatively in orderto manage the NDSMR database, a resource shared by all of the servers.Although such integrated medical networks may be restricted to aparticular geographical region, due to differing medical jurisdictionswithin a country or between different countries, it is an integrationhurdle which could eventually be overcome as a result of a concept ofthe current invention known as an individual's biological signature, tobe described in detail below. The integration of medical facilitiescould thus someday be national wide, or even international wide, therebyenlarging and improving the health network.

FIG. 4 is a flowchart depicting the improved diagnosis process as aresult of the present invention. Assume that an ambulance delivers anunconscious patient to Hospital A at step 400. Also assume that thepatient is a network user of the health network, and therefore has apersonal file stored in the NDSMR database. After the doctor makes aninitial diagnosis at step 402, the patient is checked for identificationat step 404.

If the patient does have identification, his/her network validated orattributed identifier will be known at step 408. In the most preferredembodiment of this invention, such an identifier consists of thepatient's medical insurance number such as the one available in a numberof countries of the world, including Canada. Alternatively, theidentifier may consist of the patient's social insurance number, SmartCard, or any other network-attributed identification. A Smart Card is anintegrated circuit-based card containing individual specific medicalinformation, to be read from and written to by appropriate electronics,and offers several implementation alternatives to the NDSMR system, tobe described in more detail below. If the patient does not haveidentification, his/her biological signature can be obtained as auniversal identifier at step 406. In a particular example ofimplementation of this invention, such an identifier consists of afingerprint-derived signature. Different types of software-basedtechnology for the implementation of system user identification via afingerprint-derived biological signature exist and are currentlyavailable on the marketplace. Alternatively, the identifier may consistof a patient's retinal or genetic-derived signature, or any other typeof biological signature.

At step 410 the doctor sits down at workstation 304 and logs onto theserver 300, as will be discussed below. When prompted, the doctor usesthe identifier obtained at either step 406 or step 408 in order torequest the patient's NDSMR from the server 300. The record istransmitted from the NDSMR database 302 to the doctor's workstation atstep 412. Once the doctor has read the pertinent medical informationfound in the record, he/she can scan a list of pointers appended to therecord. As will be further described below, these pointers representvarious significant medical documents (such as x-rays, surgical reports,etc.), and by their textual or visual representation allow the doctor todetermine which of the pointers refer to documents pertinent to thepatient's current medical condition. Specific to this example, thedoctor decides at step 414 that a pointer referring to the most recentelectrocardiogram taken at Hospital B would be helpful for diagnosis,and at step 416 he/she activates the corresponding pointer.Consequently, the document is downloaded over the health network fromHospital B's LAN to the doctor's workstation. This document allows thedoctor to make a second diagnosis based on the patient's complete andmost recent medical history at step 418.

FIG. 5 is a general representation of the client-server architecturethat implements the NDSMR system. The system includes three maincomponents, notably the client 304, the server 300, and the NDSMRdatabase 302. In both client 304 and server 300, the basic software isan operating system running on the hardware platform. The platforms andthe operating systems of the client and server may differ. Indeed, a keycomponent of the NDSMR system is that through client-server computing amultitude of different types of operating systems may exist within thevarious medical facility LANs. As long as the client 304 and server 300share the same communication exchange protocols and support the sameapplications, the lower-level differences are irrelevant. It is thecommunications software which enables clients and server tointeroperate. Specific to the NDSMR system, the communication exchangeprotocol adopted will be an open, non-proprietary protocol, for instancethe Internet Protocol, a standard exchange protocol in client-servernetworking, or any other similar progressive communication exchangeprotocol.

For the purpose of this specification, the term interoperate implies,among other things, the ability of different system users (clients) toshare server information and have on-line consultations, in both realand delayed time. Real-time computing is defined as the type ofcomputing in which the correctness of the system depends not only on thelogical result of the computation but also on the time at which theresults are produced. Real-time tasks therefore attempt to control orreact to events that take place in the outside world. As these eventsoccur in “real time,” a real-time task must be able to keep up with theevents with which it is concerned. On the other hand, delayed-time tasksare not at all concerned with the outside world events, delayed-timesystem correctness depending solely on the logical result of thecomputation.

The benefits of real-time medical consultations in the case ofemergencies are very clear. For example, consider a doctor at Hospital Cconferring with a doctor at Hospital D that is remote from Hospital C.Both doctors can share access to an individual's NDSMR, simultaneouslystudying the record, visible on both of their workstations, andcommunicating in real-time with each other via some sort of text, voice,or video communications link, for instance an Internet messaging window,from their workstations. The equipment necessary to allow for suchreal-time communication will not be described in detail, as there are avariety of products available on the market that could be used for thistask and that are well-known to persons skilled in the art.

The server 300 is responsible for maintaining the NDSMR database, forwhich purpose a database management system module is required. A varietyof different applications that make use of the database may be housed onthe client machines. The operative relationship that ties clients, suchas client 304, and server 300 together is software that enables a clientto make requests to the server 300 for access to the NDSMR database 302.It is important to note that the division of work between a client 304and server 300 may be allocated in a number of ways. In a preferredembodiment of this invention, the system implements cooperativeprocessing, whereby the application processing is performed in anoptimized manner by taking advantage of the strengths of both client andserver machines and of the distribution of data. Although such aconfiguration is quite complex to set up and maintain, in the long runthis configuration offers greater user productivity gains and greaternetwork efficiency.

Alternatively, the system may be implemented with server-basedprocessing or client-based processing. In server-based processing, themost basic class of client-server configuration, the client is mainlyresponsible for providing a user-friendly interface, whereas nearly allof the processing is done on the server. In client-server processing,virtually all of the application processing is done at the client, withthe exception of certain data validation routines and other databaselogic functions that are best performed at the server. This latterarchitecture is perhaps the most common client-server approach incurrent use. In the interest of clarity, the server-based processingimplementation is described in the remainder of this description;however, the NDSMR client-server division of work may be any one of theoptions described above.

FIG. 7 is a more detailed block diagram of a preferred embodiment of theserver 300, which has the responsibility of managing, sorting, andsearching the NDSMR database 302. Towards this end, the server isprovided with a memory 720, high-speed processor/controllers 708, 710,and 712 (assume for this example that there are three), and a high-speedinput/output (I/O) architecture. The I/O architecture consists of theinterfaces 702, 704, and 706. An internal system bus 711 interconnectsthese components, enabling data and control signals to be exchangedbetween them. The server has 6 ports, identified as port A, port B, portC, port D, port E, and port F. These ports connect the server tophysical links 1, 2, and 3, allowing data to be transported to and fromvarious clients within the network. In the example shown, ports A, B,and C are input ports on the physical links 1, 2, and 3, respectively,while ports D, E, and F are the output ports on those same physicallinks. The input ports are designed to receive data from theirassociated physical links, while the output ports are designed totransmit data over their associated physical links.

The interfaces 702, 704, and 706 interconnect various input and outputports to the physical links 1, 2, and 3, respectively. Their function isto transmit incoming data packets to the internal system bus 711 fortransport to the memory 720 where they can be processed by one of theprocessors. On the output side, the interfaces are designed to acceptdata packets from the system bus 711 and impress the necessaryelectrical signals over the respective physical links so that the signaltransmission can take effect. It is not deemed necessary to discuss thisstandard operation of the interfaces 702, 704, and 706 in more detailbecause it is well known to those skilled in the art and is not criticalto the success of the invention.

The memory 720 contains a program element that controls the operation ofthe server. That program element is comprised of individual instructionsthat are executed by the controllers, as will be described in detailbelow. The program element includes several functional blocks thatmanage several tasks. One of those functional elements is the DatabaseManagement System (DBMS) 714 which provides efficient and effective useand maintenance of the NDSMR database 302. The DBMS will not bedescribed in detail because it is well known to those skilled in thetechnological field to which the present invention belongs.

Besides the program element, the memory also holds the usual routingtable that maps the destination addresses of incoming IP data packets(inherent to the IP communications exchange protocol) to the serveroutput ports. It is not deemed necessary to discuss the structure of therouting table here because this component is not critical for thesuccess of the invention and also it would be well known to a personskilled in the technological field to which the present inventionbelongs. The memory also provides random access storage, capable ofholding data elements such as data packets that the processorsmanipulate during the execution of the program element.

Another component stored in the memory 720 is a validation table, whichmaps all of the registered user IDs to corresponding passwords. Thetable is used to validate clients logging on to the server, for securitypurposes. One of the characteristics of cooperative or client-basedprocessing is that a system feature such as user validation would notnecessarily be exclusive to the server, but could also take place, inwhole or in part, at the client workstation. This would remove from theserver a part or all of the burden of dealing with invalid clients, thusincreasing system speed and efficiency. The identification tableassociates with each user a unique user profile that specifiespermissible operations and NDSMR accesses, in order to limit access todata held within the database. Specifically, the table is used toidentify between clients with different user privileges, for instanceclients with archivist status as opposed to basic user status. Archiviststatus accords the client with read and write status, including editingand modifying privileges, for updating the NDSMRs. User status limitsthe client to NDSMR read status only. Finally, the memory 720 contains arequest queue which is a buffer memory space of the FIFO type, althoughalternative types of buffer memory space may also be used, that can holddata packets to be sent to one of the controllers for processing. Thephysical configuration of the buffer does not need to be described indetail because such a component is readily available in the marketplaceand the selection of the appropriate buffer mechanism suitable for usein the present invention is well within the ability of a person skilledin the art.

In a most preferred embodiment of this invention, the NDSMR database 302is part of the memory 720 of the server 300, as shown in FIG. 7. In thisembodiment, the NDSMR database 302 is actually on a separate storagemedium, such as a non-volatile medium interconnected through ahigh-speed data bus with the memory 720 so the record set from thedatabase 302 can be quickly loaded in the random access memory 720 forprocessing. Alternatively, the collection of data which makes up theNDSMR database 302 may be stored remotely on one or a set of physicalstorage device(s), for instance a disk. In such a case, one of theserver's device drivers would be responsible for communicating directlywith the peripheral device(s) in order to access the database.

FIG. 8 provides a complete flowchart illustrating an example of theoperation of the program element stored in the memory 720, and executedby any one of the processor/controllers, that regulates the operation ofthe server 300, specifically its interaction with the clients as well aswith the NDSMR database 302. Although the server program is running atall times, if no clients are logged on to the server then it is in aneffective perpetual wait state, shown at step 800. Once a clientattempts to log on, at step 802, control is passed to the validationfunctional block that is part of the program element in order to ensurethat the client is a server-registered user at step 804. Validationconsists simply in ensuring that the user's ID is known to the system(exists within the validation table) and that the user knows the correctpassword associated by the system with that ID (mapped by the validationtable). If either the user's ID is not known to the system, or thepassword given is incorrect, validation will fail and the user refusedpossibility of logging on to the server. This is a basic validationprocedure that is widely used. More complex validation methods can beimplemented if the level of security demands it.

Next, the server waits for a request from any of the logged on clientsat step 806. When a request does occur, it arrives as a flow of datapackets at interface 702, 704, or 706, over physical link 1, 2, or 3,respectively. The request is confirmed at step 808. At step 810, therequest is stored in the request queue found in memory 720, to await itsturn for processing. The program element next releases a request fromthe queue (the oldest request) to any non-busy processor. If all of theprocessors are occupied, the release step 812 is delayed until one ofthe three processors is available.

Once a request has been released to a processor, the program elementreaches step 814, whereby the requesting client is identified by theidentification logic stored in memory 720. The identification logicfirst reads the request data packet header in order to determine thedestination address for the response to the request, specifically theaddress of the requesting client which is read from the source field,and second assigns correct status to the client (user, archivist, orother status). This status is determined by the user profile, read fromthe identification table stored in memory 720. Step 814 also includesrouting logic, whereby the routing table is accessed in the memory 720in order to determine the correct output port for transmitting adatabase response to the particular client.

At step 816, the processor must determine the search parametersspecified by the request. These parameters consist of a patient'sidentifier and/or a list of other qualifiers (for instance a particulartreatment, medical condition, age group, sex, etc). Control is passed tothe DBMS logic at step 818, at which point the search is performed onthe NDSMR database. The DBMS not only performs the search on all datacontained within the NDSMR database, but also controls access tospecific records or even portions of records within the database,ensuring that confidential data or specific confidential parts of thedata being accessed are masked when returned to the client, based on theuser profile determined at step 814. The data returned by the NDSMRdatabase search are transmitted over the pre-determined output port andto the appropriate client at step 820.

As indicated above, an aspect of the current invention is theuser-friendly interface provided at the client workstation 304. Thisinterface facilitates the user's attempts at making requests of theserver, through easy-to-follow prompts and an on-line knowledge systemto help the user with any questions or problems. The interface allowsthe user to perform searches or queries on the NDSMR database, usinginformation filters to simplify the extraction of pertinent data fromwhat may be hundreds of thousands of network-distributed shared medicalrecords.

The interface also allows the user to perform keyword-basedInternet-wide searches, transparent to the user. For example, aworkstation user could initiate an Internet search for all documentsrelating to a particular medical condition by simply inputting the nameof the medical condition as the keyword, the search results returned tothe user being a list of hypertext links to all corresponding Internetdocuments. Note that different software packages for implementing suchan interface feature exist and are currently available in themarketplace.

Finally, the interface offers text-processing tools, necessary to theediting, publishing, and merging of all data received from both theInternet and the server 300. Future variations to the NDSMR system mayinclude a more progressive interface at the client workstation.Specifically, a three-dimensional view of the human body may beavailable to doctors and consultants logged on to the NDSMR server, usedfor making requests, medical enquiries, and searches.

The Network Distributed Shared Medical Record itself is another element.The NDSMR is an evolving summary medical document for a particularindividual, integrated in the form of a network accessible document. By“summary” it is meant that the record does not necessarily contain allthe information currently found in local network medical archives.Rather, the record is a compendium of critical medical informationpertinent to a particular individual, potentially useful in the medicaldiagnosis of an individual's state of health and correspondingtreatment. The NDSMR is therefore a shared minimal record, offering acommon communication interface to medical facilities that may be usingincompatible information systems. It has the merit of being able to beconsulted easily, at a distance, on an emergency basis, as opposed tothe current situation of files archived in a local network butinaccessible to any users in other networks.

In a preferred embodiment of this invention, the NDSMR includes at leastone universal or network-attributed identifier, distinguishing onerecord from another, and a dynamically updated list of biological datapertinent to the individual, accessible by pointers referring to thelocal network where the data is actually being stored. This biologicaldata consists of significant medical documents in an electronic formatsuch as laboratory tests, x-rays, surgical reports, electrographic data,etc. Alternatively, other embodiments of the NDSMR may also include avariety of other medical information pertinent to the individual.

FIGS. 6A, 6B, and 6C display a possible layout for the NDSMR as a WWWdocument, presenting several categories of medical information pertinentto an individual, in this example John Doe. The individual's identifieris indicated at the top of the record, as seen in FIG. 6A. FIGS. 6B and6C display other categories of information, including:

-   -   administrative medical data (date of birth, home and work        address and phone number, emergency contact, regular physician,        etc.);    -   permanent biological data (blood type, genetic markings or        deficiencies, tissue antigens, etc.);    -   significant antecedents (family medical history, personal        medical history, surgical history, etc.); and    -   current medical condition (allergies, medication, etc.).

The final category seen in FIG. 6C consists of the dynamically updatedlinks to other biological data. The eight pointers listed refer to othermedical documents pertinent to John Doe which are maintained indifferent local networks, and which can be downloaded from anothernetwork site to the client workstation by invoking the downloadingoperation embedded in the pointer, thus specifying the address of thesite (and if necessary of a particular file at that site).

In addition to the set of pointers, the NDSMR could also offer access tocomplementary external sources of information, transparent to theworkstation client. Potential sources could be pharmacy networks,medical libraries or journals, accessible to the doctor or consultantvia references within the NDSMR seen on their workstation. Assume aconsultant has downloaded John Doe's NDSMR from the server 300, and isverifying the Medication(s) Used reference under the Current MedicalCondition category, seen in FIG. 6C. When the consultant invokes theMedication(s) Used reference, for instance by clicking with the computermouse on the hypertext link, the NDSMR system will automaticallygenerate user authorization in order to access an Internet publishedMedical Library that may be held on an Internet site containing thisinformation, thus allowing the consultant to look up the specificsconcerning John Doe's current medication.

In accordance with this invention, the data structure of the pointerallows the workstation user, such as a doctor or consultant, todetermine the general nature of the information to which the pointer isreferring. In other words, the doctor can tell by simply looking at thepointer whether it points to a medical document concerning a pulmonaryx-ray, an electrocardiogram, allergy tests, etc. In a preferredembodiment of this invention, the pointer representation, as seen on thescreen of the client workstation, is as seen in FIG. 6C. The textualrepresentation of the pointer indicates clearly to the user the medicaldocument or information to which the pointer points, whether it be themost recent or a previous electrocardiogram, coronarography, x-ray, orbrain CT scan. Alternatively, the pointers may be of a graphicalrepresentation, small icons used to specify relevant body parts andillustrate medical treatments. The scope of this invention also includesall other variations of a pointer representation implementation whichreveals the nature of the information to which it points. Transparent tothe user is the actual address, hidden beneath the physicalrepresentation, which is the actual device needed for contacting anddownloading from various external LANs and other sources, to bediscussed in more detail below.

In short, the NDSMR record is a data structure that contains two typesof elements, namely a collection of medical data elements about theindividual and one or more pointers that allow additional information tobe downloaded, this additional information being of a medical nature andcomplementing the data held in the collection of medical data elements.Specific to this invention, these pointers adopt the URL (UniversalResource Locator) addressing system, which allows pointing to a specificfile in a directory, where that file and that directory can exist on anymachine on the integrated health network and can be served via any ofseveral different methods, specifically the Internet technologies suchas ftp, http, gopher, etc. The URL addressing system is well documentedand very well known to those skilled in the art, and therefore will notbe described in more detail.

Each pointer provides an address which may consist in the entire addressinformation of the file pointed to by the pointer or in a reference tothe address information, where the reference may be an index in a tablethat contains the address information. Associated directly with thepointer is a data field, possibly stored in a mapping table in thememory of the NDSMR server, where this data field contains dataindicative of the basic nature of the information held in the file orresource to which the pointer is directed. For the purposes of thisspecification, when used in the context of a pointer and a data field,the term “associated” means that the data field is either in a directone-to-one mapping relationship with the pointer or, alternatively, isintegrated with the pointer address to form the actual pointer datastructure. In a very specific embodiment, the data field associated withthe pointer, indicative of the basic nature of the information pointedto, can contain codes normally used by physicians to categorizetreatment events that they have administered to patients. Those codesare normally used for remuneration purposes, however, they can beemployed here in a satisfactory manner as indicators of the nature ofthe medical data. Alternatively, the data field associated with thepointer may also contain the date and time at which the pointer wascreated (enabling the display of the information at the clientworkstation to be effected in a chronological order), a textualdescription of the medical information pointed to, a brief descriptionof the status/results of the medical information pointed to, etc.

To facilitate the reading of the information associated with thepointers, namely the basic nature of the medical data, the display ofthe pointers may be organized and enhanced to enable the user to easilygrasp the meaning of the data without the necessity to refer to listscross-referencing codes with the basic nature of the medical data. Thiscan be accomplished in several ways. For instance, the pointers relatedto the same information, for instance containing the address of filesthat hold electrocardiograms, may be displayed on the client workstationin a separate window and arranged in that window in chronological order.Another possibility is to display beside each pointer an icon or textbox with the suitable data. This can be accomplished by providing theclient workstation with a table that maps the code in the pointeridentifying the basic nature of the medical data with the type ofinformation to be displayed to the user. When the NDSMR is loaded fromthe remote server 300, the list of pointers is identified and scanned toextract from them the codes identifying the basic nature of the medicaldata. The codes are then cross-referenced through the table with thecorresponding information to be displayed. The information is thendisplayed on the screen of the user.

Another aspect of this invention is the update of the NDSMRs, followingthe creation of new medical data. This task could be effected by a NDSMRadministrator, be it a medical archivist, webmaster, or some otheradministrative appointee, also responsible for the maintenance andregular update of a local medical information system. Taking for examplethe medical archivist, it is known that within all of the healthcareestablishments such archivists are currently responsible for ensuringmaintenance of all local medical files, as well as for producinghospitalization summaries, and therefore are aware of all recent medicalacts and treatments performed within their medical facility. Analternative to the use of NDSMR administrators is the implementation ofautomatic NDSMR updates, a process which would involve the incorporationof some sort of intelligence system into all local medical networkinformation systems.

FIG. 9 illustrates an example of a procedure to be followed by medicalfacility archivists in order to update the NDSMRs. Assume that thearchivist within a particular medical facility receives on a regularbasis, at step 900, a list of recent medical acts performed at thefacility, as well as supporting documents for these acts. At step 902,the archivist updates the facility's local Intranet medical files andcreates updated hospitalization summaries. The archivist's next step isto log on to the NDSMR server, using an archivist assigned password, atstep 904. The server and its DBMS will recognize the archivist passwordand profile and assign privileges accordingly, as described above forsteps 804 and 818 of the NDSMR server program element. For eachdifferent patient appearing on the archivist's updated list, a requestmust be made in order to retrieve the appropriate NDSMR. The request ismade on the basis of the particular patient's identifier, submitted tothe NDSMR server at step 906. At step 908, the NDSMR is downloaded tothe archivist's workstation, at which point the archivist is capable ofmodifying and updating certain sections of the data contained in theNDSMR, for instance the Significant Antecedents, Current MedicalCondition and Links To Other Biological Data categories as seen in FIG.6C. At step 910, the archivist refers to the updated list to update theNDSMR in order to reflect the individual's most recent and pertinentmedical information, treatments, and corresponding pointers. Forexample, assume that one of the archivist's list entries is that Mr.John Doe has undergone a new electrocardiogram at Hospital E. Thearchivist will then change the Most Recent Electrocardiogram referenceseen in the Links To Other Biological Data category of Mr. Doe's NDSMRto point to the Hospital E local network, more particularly to the filecontaining the digitized electrocardiogram.

It is important to note that in order for the NDSMR system to functionwithin an extended network of LANs or local Intranets, all documentsreferred to by pointers should be archived according to a specificnomenclature and be accessible outside of the LAN. In a most preferredembodiment of this invention, this specific nomenclature consists ofthat adopted by a state or national medical insurance company, thusensuring record consistency and successful searches. The pointeraddresses, transparent to the user, must also have a specific structure,to be respected by all archivists. In a most preferred embodiment ofthis invention, the structure of the pointer addresses, all the whilerespecting the URL addressing system, consists of a combination of alocal network and machine address (or domain name), a patient'sidentifier, and a code taken from a published manual of medical actcodes adopted by a state or national medical insurance company. There doexist alternatives to the specific nomenclature and pointer structureused by the NDSMR system, and the scope of this invention includes allother such variations whereby consistency is assured within the system.

Yet another feature of this invention is its use as a search/queryengine. Not only can a user perform searches for or queries on NDSMRswithin his/her own local Intranet, but also within external sources.NDSMR searches and queries may be performed on two different types ofdata, and therefore databases: nominative and non-nominative.Non-nominative medical data and databases are accessible to allauthorized users, but do not require authorization from the patientwhose personal data is being consulted. Nominative medical data anddatabases require search authorization from both the workstation client,typically a doctor or consultant, and the concerned patient, with theexception of situations where emergency medical care is required. Thesearch requester will be prompted for this authorization through theworkstation interface described above, the authorization comprising someform of password, biological signature, or smart card. In the case wherea search is performed by a user without nominative search authorization,the NDSMR Database Management System (DBMS) will automatically mask anynominative data found in the database response before transmitting it tothe client workstation. In summary, the NDSMR system permits thedelay-free consultation of pertinent information found within differentlocal files and, for authorized users, offers an integrated researchmotor which allows for non-nominative research, by object or by concept,on the whole of the accessible databases.

In a specific example, a user of the NDSMR system may perform a searchof all of the non-nominative medical data and databases accessible viathe server 300 for a particular genetic characteristic. Thus, the searchresults returned to the user by the NDSMR system in response to thisquery would comprise all NDSMRs, both local and external to the user'sIntranet, containing non-nominative medical data that share thisparticular genetic characteristic. As mentioned above, all nominativedata within these NDSMRs would be masked by the NDSMR DBMS beforetransmission of the query response to the client workstation.Advantageously, on a basis of such a query it may be possible toassociate one or more health problems or medical conditions experiencedby a known population with a particular genetic characteristic shared bythe known population, thus furthering medical research.

For the purposes of the present description, the expression “medicalcondition” means a state of health of an individual, and may include adisease with which the individual is afflicted as well as a medicaltrait or a medical characteristic proper to the individual. In aspecific example, the medical condition found to be associated with agenetic characteristic is a medical disease, such as Alzheimers,diabetes, or depression, among many other possibilities. Alternatively,the medical condition may be a particular cholesterol level, aparticular blood pressure level, or a particular body mass index, amongmany other possibilities.

In a preferred embodiment of the invention, the NDSMR includes geneticdata for the respective individual, allowing elaborate genetic researchto be conducted by a user of the NDSMR system. In a specific example,the genetic data are stored in the NDSMR database and maintained by theNDSMR server. More specifically, one or more medical data elements ofthe summary medical record consist of genetic data. Alternatively, thegenetic data are stored remotely from the NDSMR server, in one or moredifferent local networks. In the latter case, one or more pointers ofthe NDSMR provide links to the remotely stored genetic data, allowing auser of the NDSMR system to download and access the genetic data.

In yet another alternative, genetic data for a respective individual areneither stored in the NDSMR database nor maintained by the NDSMR server.Rather, the genetic data are stored in one or more electronic databasescontaining records for a plurality of individuals, where the one or moreelectronic databases are separate from the NDSMR system but are designedsuch that the records are indexed using the same unique identifiers asthose used by the NDSMR system. Each record of such an electronicdatabase stores genetic data associated with a respective individual,and possibly other medical information for the same individual. As inthe case of the unique identifier in the NDSMR medical records, theunique identifier in the electronic database distinguishes oneindividual's record from another and is used to access the informationfor a particular individual. Examples of unique identifiers include anindividual's biological signature, medical insurance number, socialinsurance number, and Smart Card. Similarly to the NDSMRs, the recordsof these one or more separate electronic databases are regularlyupdated, such that each record includes a compendium of genetic data forthe associated individual.

In the latter case, when the genetic data for an individual are storedin an electronic database that is separate from the NDSMR system,genetic research performed by a user would include querying both theNDSMR system and the electronic database. In a possible example, theuser would first submit a query to the NDSMR system for the NDSMRsassociated with all individuals afflicted with a particular healthproblem. Next, the user would retrieve from the electronic database thegenetic data for all of the particular individuals identified by thefirst query of the NDSMR system, on the basis of the unique identifiersof these particular individuals.

Advantageously, since the NDSMR system maintains and provides supportingdiagnostic information, such as electrocardiogram, coronarography,x-ray, brain CT scan, or allergy tests, in addition to actual diagnosedmedical conditions for each patient, the NDSMR system allows forconclusive genetic research results, as opposed to the more commonpreliminary or probable results. More specifically, a genetic researchstudy may be conducted not only on the basis of patients' genetic dataand diagnosed medical conditions, but also on the basis of supportingdiagnostic information, which leads to a more exhaustive study and moreaccurate conclusions.

It should be noted that the above-described NDSMR system is but oneexample of a system and method for electronically managing medical datain order to facilitate genetic research on this medical data. Simplyput, any electronic database modeled after the NDSMR database, or anyhealth Intranet providing distributed medical information that ismodeled after the NDSMR system, will facilitate complex geneticresearch. As long as, for each individual, the electronic medical datamanagement system includes at least one universal or network-attributedidentifier, medical information pertinent to the individual, and geneticdata pertinent to the individual, the electronic medical data managementsystem will provide enhanced genetic research capabilities.

Such an electronic database or health Intranet may include a medicalrecord database similar to the NDSMR database, where each medical recordnecessarily includes at least one universal or network-attributedidentifier distinguishing one record from another, genetic data, andmedical information pertinent to the individual associated with therecord. Alternatively, the genetic data may be stored remotely from themedical records, in a separate dedicated or non-dedicated electronicdatabase, indexed by the same identifiers as used within the electronicdatabase or health Intranet. The medical information stored in themedical record may be in the form of:

-   -   textual data;    -   textual data and a dynamically updated list of biological data        pertinent to the individual;    -   textual data and graphical data; and    -   textual data and multimedia information,    -   among other possibilities.

As in the case of the NDSMR system, the biological data may consist ofsignificant medical documents in an electronic format, such aslaboratory tests, x-rays, surgical reports, electrographic data, etc.,which provide supporting diagnostic information. In a specific example,this biological data is accessible by one or more pointers stored in themedical record, where these pointers address one or more remotedatabases where the data are actually being stored.

Many different formats of genetic data exist and may be used by theNDSMR system or any other health Intranet or electronic database withoutdeparting from the scope of the present invention. Examples of possibleformats for the genetic data stored in or accessible by the NDSMR or anyother health Intranet or electronic database include the following fourformats:

1) Entire Sequence or Segment(s) of Chromosomal and/or MitochondrialGenome

As is well known, the genome of an organism is defined as all geneticinformation or hereditary material possessed by an organism. In humansand other higher life forms, the total genome is made up of both thechromosomal genome and the mitochondrial genome. Whereas the chromosomalgenome is genetic information found within chromosomes inside thenucleus of a cell, the mitochodrial genome is genetic information foundwithin mitochondrial chromosomes outside the nucleus of a cell.

2) Single Nucleotide Polymorphisms (SNPs)

The majority of the DNA sequence variation responsible for humanvariation in the genome is due to a limited number of common variantsknown as SNPs. Polymorphisms are differences in the genomic DNAsequences that naturally occur in a population. SNPs are particular DNAsequence variations that occur when a single nucleotide (A, T, C, or G)in the genome sequence is altered. Such variations can be used to trackinheritance in families.

3) SNP Haplotypes or SNP Haplotype Tags

SNPs have been estimated at 10,000,000 in the human genome, or one per300 genome base pair (bp). But not all possible combinations of SNPsoccur in humans. Findings suggest that variations are not uniformlydistributed in the genome; rather variations may occur in blocks withclustering of variations into common subtypes. SNP haplotypes consist ofa grouping of SNPs in linkage on a chromosomal segment, and have thepotential to capture the majority of the variations present within andbetween human populations. A minimal selection of SNPs that have themost discrimination power for haplotype identification are namedhaplotype tagging SNPs or htSNPs. Because of the linear nature of DNA,the variation observed at SNP haplotypes is determined by recombinationevents along chromosomes and by the historical filial structure of humanpopulations.

It is possible to retain much of the information of haplotypes byretaining only a reduced subset of markers. If the haplotype structureis identified across the genome, and if one marker is studied for eachhaplotype, then it will not be necessary to test all 10,000,000 commonvariants. In fact, haplotype tagging SNPs have the potential to reducethe total number of informative genomewide SNPs from 10,000,000 toapproximately 500,000 informative tags. The reduction in the number ofinformation tags therefore enables substantial information compression,and can facilitate the analysis of genetic susceptibility to commonmedical diseases.

4) Polymorphic Markers

A polymorphic marker displays variability in the population, therebyallowing its inheritance to be followed. In general, a genetic marker isa segment of DNA at a known physical location on a chromosome, such asVNTRs (Variable Number of Tandem Repeats). The marker can be used totrack the inheritance pattern of genes that have not yet beenidentified, but whose approximate locations can be inferred using themarkers.

In a specific, non-limiting example of implementation, an adaptiveexpert system is used in conjunction with the NDSMR system forperforming genetic research on the basis of medical and genetic datastored in the NDSMR database. Typically, an association model is firstdeveloped by the adaptive expert system, for the purposes of determiningan association that may exist between the stored genetic data and amedical condition. Next, the adaptive expert system is capable ofevaluating the possible contribution of any genetic data added to theNDSMR database under a new data field. Thus, by evaluating the medicaland genetic data stored in the NDSMR database using an associationmodel, data analysis not normally achievable can be effected. Since thefunctionality and different possible implementations of such an adaptiveexpert system have been well documented and are well known to thoseskilled in the art, they will not be described in further detail in thisdocument.

Note that the adaptive expert system may be integrated into the NDSMRserver or, alternatively, may be implemented as a stand-alone system incommunication with the NDSMR server. In the case where genetic data arestored and maintained by one or more electronic databases separate fromthe NDSMR system but indexed using the same unique identifiers as theNDSMR system, the adaptive expert system would be used in conjunctionwith both the NDSMR system and the separate electronic databases forperforming the genetic research.

It should also be noted that a similar relationship between an adaptiveexpert system and the medical record database(s) can be conceived forthe different possible types of electronic medical data managementsystems described above (i.e. health Intranet, electronic database,etc.).

As is well known, association models for adaptive expert systems arebuilt using statistical association methods. In the context of thepresent invention, association methods may be used to associate healthproblems with genetic characteristics that are shared by an affectedpopulation. One possible method for developing an integrated expertsystem for association testing is by the use of an artificial neuralnetwork (ANN).

As is well known to those skilled in the art, ANNs are computationaltools modeled on the biological nervous system with multifactorialmathematic modeling properties that can be used for the purposes ofclassification, prediction, function estimation, and pattern recognitionby capturing and representing complex input/output relationships. Morespecifically, artificial neural networks are digitized models trained byprocessing a large number of input patterns and being shown the outputpattern that resulted from each corresponding input pattern. The ANNtherefore learns how to recognize data patterns such that, once trained,the ANN is able to produce a predicted output pattern whenever it ispresented with a new input pattern never encountered before. This isespecially useful in the area of genetic research where there may be alarge amount of data to analyze, and data patterns are not as apparent.

Structurally, the ANN consists of nodal processing elements that act inparallel. Inspired by biological nervous systems, the processingelements are called neurons, while layered networks of the neurons arecalled neural networks. In a simple neural network, neurons areorganized into at least three different layers: the input layer, one ormore hidden layers, and the output layer. The input layer receives theinput, such as data from the NDSMR database. The output layer producesthe final output or target of interest in the test of association, suchas disease outcome. One or more hidden layers are found between theinput layer and the output layer, and are modeled by training the neuralnetwork. The neurons or processing elements in the ANN are connected toeach other by weighted coefficients. Therefore, the processing elementsin a particular layer depend on the data received from the processingelements in the previous layer and the weights on the connectionsbetween these two layers.

Neural networks have been extensively developed and applied as asupplement or alternative to standard statistical techniques, with someconsiderable advantages. Neural networks inherently allow for arbitrarynonlinear relations between independent and dependent variables and cantherefore model all possible interactions between variables. Standardstatistical approaches, such as logistic regression or Cox regression,would require extensive modeling to allow such interactions.

Hence, artificial neural networks are well suited to model and testassociations using the data fields of the NDSMR database. In anillustrative example, inputs to the neural network are obtained from theNDSMR database and may include genetic variables (such as SNPs),environmental factors (such as smoking status, age), or medical factors(such as medications, interventions). The outputs used to train theneural network may include health status information, such as medicaltraits and diagnosed diseases. In a specific example, the health statusinformation includes the status of an individual with regard tocholesterol level. In another example, the health status informationincludes the status of an individual with regard to cardiovasculardisease. Essentially, selected medical and genetic data of an individualare provided as input, and a status of whether or not the individualpossesses a particular medical trait or is afflicted by a particularmedical disease is used as corresponding output. A plurality of suchinput and output data must be provided in order to train the artificialneural network. The ANN is trained to predict a medical conditionoutcome, such as cardiovascular disease or high cholesterol, such that ahypothesis-based neural network model can be developed. Thus, in aspecific, non-limiting example, a predictive value of neural net inputscould be tested for association to cardiovascular disease using thehypothesis-based neural network model.

An adaptive expert system may use any suitable association method,including epidemiological studies and artificial neural networks, inconjunction with the NDSMR system for performing genetic research on thebasis of medical and genetic data stored in the NDSMR database. Theadaptive expert system would include a mathematical model built from ANNor using principal component statistics. The association model wouldallow testing of, for example, genetic factors, proteomic factors, viralinfection history, environmental factors, gene therapy, and cell ortissue grafts (allografts, autografts, or stem cell grafts) withspecific disease manifestations. Such associations may well providegenetic markers for laboratory tests, as well as specific targets(genetic, proteomic, or cell targets) for therapeutic interventionsincluding pharmacotherapeutics.

In a specific example, the adaptive expert system could be used toautomatically identify any significant contributions of newly introducedgenetic data (SNP, SNP haplotype, or marker or polymorphic marker),added to the NDSMR database under a new data field. The adaptive expertsystem would automatically evaluate the potential contribution to activeand previously defined ANN association models. Hence, it would bepossible to validate some new correlation not previously assessed, andthere would be potential for new diagnostic or therapeutic tools.

FIG. 10 displays the query usage allowed by the NDSMR system. From aclient workstation, a user may make an initial query of the server 300.The server's DBMS and database logic allow the NDSMR database 302 to besearched rapidly and efficiently. The database logic is what allows theserver to not only retrieve records on behalf of the client but also toperform searches on behalf of the client. We see in FIG. 10 that aninitial query returned 300 possible NDSMRs. The system allows the userto send out a second, more narrow query, with a resulting 25 NDSMRsreturned. The system is therefore very efficient, especially for massivesearches performed across all accessible databases. In a most preferredembodiment of this invention, the query style offered by the workstationinterface will be one of relational data searches, such as the stylecurrently offered by the Alta Vista™ web browser. The query style willnot be described in detail as it is very well known to a person skilledin the art. Alternatively, many other query styles could be incorporatedinto the NDSMR search engine, for instance an object-oriented searchstyle.

The structure of the pointers as described above, where both an addresspart and an associated data part form a pointer, allows the NDSMR systemto perform searches on all of the pointers contained within the NDSMRdatabase, representing medical files archived at all of the variouslocal networks connected within the extended health network. Asmentioned above, the data structure of the pointers allows the nature ofthe information to which they point to be determined, either directlyfrom the data structure itself in the case where both the data part andaddress part of the pointer are integrated to form the data structure ofthe pointer, or through a one-to-one mapping between the address part ofthe pointer's data structure and the data part, possibly stored in amapping table in the memory of the NDSMR server. Consequently, medicalsearches performed on the NDSMRs will return all database recordscontaining pertinent pointer links. These links will allow the user toresearch medical data from all over the health network, currentlyimpossible but vital to progressive medical development. Thus, a querycould be made to extract records based on a key relating to the basicmedical information. For example, one could extract the records of allindividuals between the ages of 25-35 that have undergone a particulartherapy. This information is particularly useful in statistical studies.

As mentioned above, the use of a Smart Card as a unique networkvalidated or attributed identifier for users of the NDSMR system offersseveral implementation alternatives to the system. In a specificalternative embodiment of the invention, the Smart Card can be used atthe client workstation in order to access the NDSMR database. Forexample, upon attempting to log onto the NDSMR system, the client, mostlikely a physician, will be prompted by the NDSMR system server (throughthe user-friendly interface seen at the workstation) to insert thepatient's Smart Card into the workstation's appropriate electronics. Theelectronics read the information contained on the card and can extractthe patient's identification. The NDSMR server's program element thenpasses control to its validation functional block in order to ensurethat the patient is a server-registered user, as described above. Inanother example, the NDSMR system server may prompt the clientworkstation user for two Smart Cards, both the physician's and thepatient's, thereby increasing the security of the system.

The Smart Card may provide more than simple user identification. Inanother alternative embodiment of the invention, a patient's Smart Cardcontains medical information specific to the patient. In one example,the NDSMR system includes the Smart Card as a storage medium for systemuser information, with the NDSMR database records consisting strictly ofat least one unique identifier and a dynamically updated list ofpointers to relevant medical information located at remote locations. Insuch a system, the patient's Smart Card would contain all other medicalinformation pertinent to the individual, for instance that shown inFIGS. 6A, 6B, and 6C (minus the Links To Other Biological Data). Uponlogging in to the NDSMR system with a Smart Card (or two), the medicalinformation stored on the patient's Smart Card would appear on theclient workstation, along with the list of pointers downloaded from thepatient's record in the NDSMR database. In another example, a patient'snominative information could all be stored on the Smart Card, with onlythe patient's non-nominative information stored in the NDSMR databasealong with the identifier(s) and the list of pointers. This particularimplementation of the system would ensure that no queries/searchesperformed on the NDSMR database revealed any confidential, nominativepatient information.

A patient's Smart Card, or alternatively any other form of portablecomputer-readable storage medium, may also be used to store and maintainall or a portion of the data found in the particular patient's NDSMR,where this data may be nominative, non-nominative, static, or dynamic.In such a situation, the NDSMR server offers a continuously availableway to update the Smart Card, the update consisting of reading thelatest information from the NDSMR and writing it to the Smart Card viathe appropriate electronics, without changing any of the static ornominative data stored on the card. This implementation would allow aphysician, at a hospital external to the NDMSR system's integratedhealth network, to have access to the individual's pertinent and mostrecent medical information, the only requirement being that the hospitalmust have the appropriate electronics to read the individual's SmartCard.

A variety of other NDSMR system implementations also exist, distributingthe whole of the patients' medical information between database recordsand patient Smart Cards or other such portable computer-readable storagemedia, and are included within the scope of this invention.

In yet another example of implementation, a personal communicationsystem (PCS), such as a cellular phone, can be used to access the NDSMRdatabase. Other examples of such a PCS include a web phone, a cellularnotepad, an IP television screen or monitor, among others. In thisexample of implementation, users of the NDSMR system, including patientsthat are registered with the NDSMR system as well as healthcareprofessionals, can benefit from convenient, mobile mechanisms foraccessing and using the NDSMR system.

In this non-limiting example of implementation, the PCS is equipped withthe same communication exchange protocol as that in use by the NDSMRserver 300, such that a connection may be established between the PCSand the NDSMR server 300. This communication exchange protocol may bethe Internet Protocol, or any other similar progressive communicationexchange protocol.

As described above, when a client attempts to log into the NDSMR system,the NDSMR server 300 will perform a validation procedure in order toconfirm that the client is a registered user of the NDSMR system. In onespecific example, this validation procedure consists of the server 300prompting the user of the PCS for an ID and password that areauthenticated by the server 300 on the basis of the validation table.Examples of such an ID include a medical insurance number, a socialinsurance number, a Smart Card, a network-attributed identifier, as wellas a digital print of the user or any other type of biologically derivedsignature.

In another specific example, the PCS provides, or itself acts as, anauthentication key to uniquely identify a particular user. In the caseof a cellular phone, each cellular phone includes a microchip that mayserve as the authentication key. For example, when the cellular phoneconnects to the NDSMR server 300, the microchip will append to therequest for connection a unique signature, recognizable by the server300 as being associated with a registered user of the NDSMR system.Alternatively, the authentication key may be a unique signature of themicrochip validated by a PIN number, where the server 300 will promptthe user of the PCS for this PIN number, or any other method of singularidentification.

In addition to an authentication key, the PCS provides the user with adisplay over which the user may view medical information and query theNDSMR system. In a specific example, the above-described user-friendlyinterface is provided by the server 300 to the display of the PCS, wherethis interface permits the PCS user to make data requests, performsearches or queries on the NDSMR database, and perform keyword-basedInternet-wide searches, among other options. In the case of a cellularphone, the screen of the cellular phone provides a medium over which acertain amount of information can be displayed. Where a large amount ofmedical information is to be requested of the NDSMR system by the user,the cellular phone may be linked to a television monitor or to apersonal or professional computer workstation, for providing the userwith a more appropriate amount of display area.

As in the case of the Smart Card, a PCS of a patient registered with theNDSMR system may include a memory device that contains medicalinformation specific to the patient. In one example, the NDSMR systemincludes the memory device of the PCS as a storage medium for systemuser information, with the NDSMR database records consisting strictly ofat least one unique identifier and a dynamically updated list ofpointers to relevant medical information located at remote locations. Insuch a system, the patient's PCS would contain, in its memory device,all other medical information pertinent to the individual. When apatient logs in to the NDSMR system via his/her PCS, the medicalinformation stored in the patient's PCS would appear on the PCS display,along with the list of pointers downloaded from the patient's record inthe NDSMR database. In another example, a patient's nominativeinformation could all be stored in the memory device of the PCS, withonly the patient's non-nominative information stored in the NDSMRdatabase along with the identifier(s) and the list of pointers. Thisparticular implementation of the system would ensure that noqueries/searches performed on the NDSMR database revealed anyconfidential, nominative patient information.

In a specific, non-limiting example, the microchip of a cellular phonebelonging to a patient registered with the NDSMR system is used as astorage medium to store and maintain all or a portion of the data foundin the particular patient's NDSMR, where this data may be nominative,non-nominative, static, or dynamic. The data stored on the microchip maybe updated on a request basis where, pursuant to logging in to the NDSMRsystem, a request is sent from the cellular phone to the NDSMR serverfor updating of the data being maintained on the microchip of the phone.Alternatively, the data stored on the microchip may be updatedautomatically whenever new pertinent medical information for theparticular patient has been archived on the NDSMR server. Specifically,the NDSMR server 300 can offer a continuously available mechanism toupdate all of the cellular phone users having subscribed to such aservice either directly, through their medical insurance company, orthrough a medical plan under which they are protected.

Taking the example of a cellular phone user that has subscribed to theservice directly, when the server 300 is performing the automatic updateit will read the latest medical information from the patient's NDSMR andwill transmit this data to the patient's cellular phone. In order toperform the data transmission, the server 300 will first attempt toestablish a connection with the patient's cellular phone. Once aconnection is established, the server 300 will transfer the pertinentmedical information to the microchip of the cellular phone, withoutchanging any of the static or nominative data stored in the microchip.

Note that, in addition to being used as a way to access the NDSMRsystem, a PCS may also be used to access any health Intranet thatprovides distributed medical information and offers to registered usersof the Intranet the possibility of connecting via a PCS. Such a healthIntranet may include a summary medical record database similar to theNDSMR database, where each summary medical record necessarily includesat least one universal or network-attributed identifier, distinguishingone record from another, as well as medical information pertinent to theindividual associated with the record. This medical information may bein the form of:

-   -   textual data;    -   textual data and a dynamically updated list of biological data        pertinent to the individual, accessible by one or more pointers        addressing one or more remote databases where the data are        actually being stored; and    -   textual data and multimedia information,    -   among other possibilities.

As in the case of the NDSMR system, the biological data that areaccessible by pointers may consist of significant medical documents inan electronic format, such as laboratory tests, x-rays, surgicalreports, electrographic data, etc.

The above detailed description of examples of implementation under thepresent invention should not be read in a limitative manner asrefinements and variations are possible without departing from thespirit of the invention. The scope of the invention is defined in theappended claims and their equivalents.

Although the invention is illustrated and described in this documentwith reference to specific embodiments, the invention is not intended tobe limited to the details shown. Rather, various modifications may bemade in the details within the scope and range of equivalents of theclaims and without departing from the invention.

1. A method for conducting genetic research on medical data, said methodcomprising: a) accessing a database storing a plurality of medicalrecords associated with a plurality of individuals, each medical recordincluding: i) at least one unique identifier associated with a certainindividual, and ii) medical data associated with the certain individual;b) extracting from said database the medical data associated with atleast a subset of the plurality of individuals; c) obtainingelectronically stored genetic data on a basis of the respective uniqueidentifier for each of said at least a subset of the plurality ofindividuals; and d) processing the extracted medical data and obtainedgenetic data for attempting to identify an association betweenparticular genetic data and a particular medical condition.
 2. Themethod as defined in claim 1, wherein, for each of said at least asubset of the plurality of individuals, the associated medical dataincludes health status information, said method including processing thehealth status information and the genetic data for attempting toidentify an association between particular genetic data and a particularmedical condition.
 3. The method as defined in claim 2, whereinprocessing the extracted genetic data and health status informationincludes generating an association model.
 4. The method as defined inclaim 3, further comprising updating said association model when newelectronically stored genetic data becomes available.
 5. The method asdefined in claim 3, including generating said association model on thebasis of principal components statistics.
 6. The method as defined inclaim 3, including generating said association model on the basis of anartificial neural network.
 7. The method as defined in claim 6, whereingenerating said association model includes training said artificialneural network.
 8. The method as defined in claim 7, wherein trainingsaid artificial neural network includes providing input and outputtraining data to said artificial neural network, said input trainingdata including the genetic data and said output training data includingthe health status information.
 9. The method as defined in claim 1,wherein, for each of said at least a subset of the plurality ofindividuals, the associated medical data includes disease statusinformation, said method including processing the disease statusinformation and the genetic data for attempting to identify anassociation between particular genetic data and a particular medicaldisease.
 10. The method as defined in claim 1, wherein said step ofobtaining electronically stored genetic data associated with eachrespective unique identifier includes extracting from said database thegenetic data associated with said at least a subset of the plurality ofindividuals.
 11. The method as defined in claim 1, wherein said databaseis a first database, said step of obtaining electronically storedgenetic data associated with each respective unique identifier includesaccessing a second database storing a plurality of medical filesassociated with respective individuals, each medical file including: i)said at least one unique identifier associated with the respectiveindividual, and ii) genetic data associated with the respectiveindividual.
 12. The method as defined in claim 1, wherein each medicalrecord further includes: a) at least one pointer, said pointer using aURL addressing system to indicate the address of a location containingmedical data not included in the medical record for the certainindividual, the address being in a form allowing a machine to access thelocation and import the medical data from the location, and b) at leastone data field, said data field associated with said pointer, said datafield being indicative of the particular nature of the medical data atthe location pointed to by the pointer; said step of extracting fromsaid database the medical data associated with at least a subset of saidplurality of individuals including importing the medical data from thelocation pointed to by said at least one pointer.
 13. The method asdefined in claim 1, wherein the step of obtaining electronically storedgenetic data associated with the respective unique identifier includesobtaining genetic data in a format selected from one of a segment of asequence of patient chromosomal genome, an entire sequence of patientchromosomal genome, a segment of a sequence of patient mitochondrialgenome, an entire sequence of patient mitochondrial genome, an entiresequence of patient chromosomal and mitochondrial genome, a singlenucleotide polymorphism (SNP), a SNP haplotype, a SNP haplotype tag, ora polymorphic marker.
 14. A method for conducting genetic research onmedical data, said method comprising: (a) accessing a database storing aplurality of medical records associated with a plurality of individuals,each medical record including: (i) at least one unique identifierassociated with a certain individual, (ii) medical data associated withthe certain individual, said medical data including health statusinformation, and (iii) genetic data associated with the certainindividual; (b) extracting from said database the health statusinformation and the genetic data associated with at least a subset ofsaid plurality of individuals; and (c) processing the extracted medicaldata and genetic data for attempting to identify an association betweenparticular genetic data and a particular medical condition.
 15. A methodfor conducting genetic research on medical data, said method comprising:a) accessing a database storing a plurality of medical recordsassociated with a plurality of individuals, each medical recordincluding: i) at least one unique identifier associated with a certainindividual, and ii) medical data associated with the certain individual,said medical data including health status information; b) extractingfrom said database the health status information associated with atleast a subset of said plurality of individuals; c) obtainingelectronically stored genetic data associated with the respective uniqueidentifier for each of said at least a subset of said plurality ofindividuals; and d) providing the genetic data and health statusinformation to an adaptive expert system, said adaptive expert systemcapable of processing the genetic data and health status information forattempting to identify an association between particular genetic dataand a particular medical condition.
 16. A method for conducting geneticresearch on medical data of a network system, said network systemincluding at least one server managing a database, said databasecontaining a plurality of medical records associated with respectiveindividuals, said method comprising: a) including in each medical recordat least one unique identifier associated with a certain individual anda collection of medical data elements associated with the certainindividual, said collection of medical data elements including geneticdata and health status information; b) accessing at least a subset ofsaid medical records stored in said database; c) extracting the geneticdata and health status information from said at least a subset ofmedical records; and d) providing the extracted genetic data and healthstatus information to an adaptive expert system, said adaptive expertsystem capable of processing the extracted genetic data and healthstatus information for attempting to identify an association betweenparticular genetic data and a particular medical condition.
 17. Incombination: a) a network server having a first database storing aplurality of medical records associated with respective individuals,each medical record having: i) at least one unique identifier associatedwith a certain individual, and ii) a collection of medical data elementsassociated with the certain individual, said collection of medical dataelements including health status information; b) a second databasestoring a plurality of medical files associated with respectiveindividuals, each medical file having: i) said at least one uniqueidentifier associated with the respective individual, and ii) geneticdata associated with the respective individual; and c) an adaptiveexpert system able to extract from said first and second databases thehealth status information and genetic data associated with at least asubset of individuals, said adaptive expert system operative to processthe extracted genetic data and health status information for attemptingto identify an association between particular genetic data and aparticular medical condition.
 18. In combination: a) a network serverhaving a database storing a plurality of medical records associated witha plurality of individuals, each medical record having: i) at least oneunique identifier associated with a certain individual, and ii) acollection of medical data elements associated with the certainindividual, said collection of medical data elements including healthstatus information and genetic data; and b) an adaptive expert systemable to extract from said database the health status information andgenetic data associated with at least a subset of said plurality ofindividuals, said adaptive expert system operative to process theextracted genetic data and health status information to attempt toidentify an association between particular genetic data and a particularmedical condition.
 19. A network server, comprising: I) a processor; andII) a memory including: A) a plurality of medical records associatedwith respective individuals, each medical record having at least oneunique identifier associated with a certain individual and having acollection of medical data elements associated with the certainindividual, said collection of medical data elements including geneticdata; B) a program element including individual instructions forexecution by said processor, said program element being responsive to agenetic research query issued by a client connected to said serverthrough a data communication pathway for: (1) identifying at least asubset of said plurality of medical records, (2) extracting at least aportion of said collection of medical data elements from each identifiedmedical record, said at least a portion of said collection of medicaldata elements including selected genetic data associated with therespective individual, and (3) transferring said at least a portion ofsaid collection of medical data elements towards the client over thedata communication pathway.
 20. The network server as defined in claim19, wherein each said medical record further has: a) at least onepointer, said pointer using a URL addressing system to indicate theaddress of a location containing medical data not included in themedical record for the certain individual, the address being in a formallowing a machine to access the location and import the medical datafrom the location; and b) at least one data field, said data fieldassociated with said pointer, said data field being indicative of theparticular nature of the medical data at the location pointed to by thepointer.